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Mathew Mervin Psy 202 Exam #1 Study Guide

by: Zoe Notetaker

Mathew Mervin Psy 202 Exam #1 Study Guide Psy 202

Marketplace > University of Mississippi > Psychology (PSYC) > Psy 202 > Mathew Mervin Psy 202 Exam 1 Study Guide
Zoe Notetaker
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About this Document

This covers all the material on the first exam! It includes all vocabulary words and I followed Professor Mervin's study guide when creating the chapter walk through. Good luck and have fun studying!
Elementary Statistics
Dr. Mervin Matthew
Study Guide
50 ?




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This 5 page Study Guide was uploaded by Zoe Notetaker on Monday September 12, 2016. The Study Guide belongs to Psy 202 at University of Mississippi taught by Dr. Mervin Matthew in Fall 2016. Since its upload, it has received 40 views. For similar materials see Elementary Statistics in Psychology (PSYC) at University of Mississippi.

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Date Created: 09/12/16
Exam 1 Psy 202 Study Guide  Vocabulary Words:  Qualitative Research ­ Uses summaries, unstructured, draws conclusions; in short, quality  information and deeper thinking    Quantitative Research ­ Uses structured data, statistics, and objective conclusions; in short, it  uses numbers    Experiments ­ A form or research in which a prediction is tested    External Validity ­ Deals with whether or not the same effects that occurred in the lab will be the  same in the outside world    Random Assignment ­ Test subjects are randomly assigned to control or test groups    Quasi­Experiment ­ An experiment that cannot use random assignment; the subjects assign  themselves    Observational Study ­ A study in which subjects are observed and not interfered with by the  experimenter    Population ­ The entire group of people one is trying to generalize     Samples ­ A subset of a population in which one is interested and can test    Simple Random Sampling ­ All people in a population have equal chances of being sampled    Stratified Sampling ­ ​divides the population into separate groups, called strata. Then, a  probability sample ( ​ often a ​simple random sample ) ​  is drawn from each group    Cluster Sampling ­ Occurs when a population is composed of sub groups and subjects are then  taken from each sub group    Systematic Sampling ­ Takes every nth person (not everyone has a chance in this method)    Deliberate/Purposive Sampling ­ Occurs when one subset is targeted more than another    Convenience Sampling ­ People in a sample are those that are easiest to recruit    Population Parameters ­ (Uses greek letters) Shows characteristics of a population    Sample Statistics ­ (Uses english letters) shows information and characteristics of the sample,  not the entire population  Independent Variable ­ The one being manipulated by the experimenter    Dependent Variable ­ The variable being measured or changed    Qualitative ­ Categorical information    Quantitative ­ Numerical information and data    Discrete ­ No fractional amounts, only whole numbers, not infinite    Continuos ­ Has fractional amount, infinitive    Construct ­ Using body/ other behavior to infer something    Nominal Scales ­ Only gives categorical information    Ordinal Scales ­ Gives categorical information, and ranks the categories    Interval Scales ­ Gives categorical, rank, and distance information    Ratio Scales ­ Category, rank, distance, and uses true zero    Reliability ­ Getting the same results repeatedly    Validity ­ Measuring what one actually intends to measure    Confounds ­ Outside variables that affects the dependent variable    Central Tendency ­ The score around which all other scores cluster    Variability ­ How spread out the scores are (from the central tendency)    Skewness ­ How spread out equal sections of distribution are from each other    Kurtosis ­ The highest point on a graph    Mode ­ Score that occurs most often in a set of data    Median ­ Value that divides the distribution in half (Number in the middle)    Mean ­ Average of all scores    Range ­ Highest score minus the lowest score    Interquartile Range ­ Gets rid of the best and worst scores by using middle quartiles    Average Deviation­ The average of all deviation scores in a set of data    Variance­ A method of calculating deviation from the means of a group    Standard Deviation­ Square root of the variance    Degrees of Freedom­ How many scores are free to do what they want    Symmetry­ Measure of skewness    Curvature­ Measure of kurtosis    Box and Whisker Plot­ A graph in which one or more distributions is broken into quartiles    Bar Chart­ Displays noncontinuous data and deals with categorical scores    Pie Charts­ A circle that is sliced to represents percentages    Index of Qualitative Variation­ A measure of statistical dispersion in nominal distribution    Percentile Rank­ Uses raw scores and convert them into cumulative relative frequency    Percentile­ Converts cumulative relative frequency into raw scores    Z­Transformation­ (z­scores) the standardized scores    Study Guide By Chapter:  Chapter 1  Experiments v. quasi­experiments v. observational designs  ● An experiment is a form of research that uses random assignment when testing a  hypothesis. A quasi­experiment is unable to use random assignment. An observational  design prevent the experimenter from interfering with the test subjects.  Populations v. samples  ● A population is the entire group of people one is trying to generalize, and the sample is  the subset of the population in which one is actually testing  Look over different types of sampling techniques  ● Written above  Independent v. dependent  ● The independent variable is the one that is being manipulated by the experimenter and  the dependent is the variable one is measuring.  Qualitative v. quantitative  ● Qualitative refers to dealing with categorical information while quantitative uses numbers  Continuous v. discrete  ● Continuous data uses fractional amounts and is infinite (qualitative) and discrete data  only has whole numbers because there is a set number of categories (quantitative)  Nominal, ordinal, interval, ratio  ● Nominal scales only give a person categorical information, there is no inbetween options  or natural order. Ordinal scales give both categorical information and rank the  categories. Interval scales give categorical, rank, and distance information. Ratio scale  give the most info: categorical, rank, distance, and the true zero.  Reliability (in general)  ● An experiment is reliable if it is redone and the same results are achieved repeatedly  Validity (in general)  ● An experiment is valid if one measures what they intend to and not any confounds  Chapter 2  Frequency tables  ● Simple frequency tables have 2 columns and include all possible values, more columns  are added as the frequency type changes and becomes more complex  Relative frequency, and cumulative frequency  ● Relative frequency is simple frequency divided by the total number of scores; absolute  frequency is normalized by total number. Cumulative frequency looks at the scores  above or below a distribution  Ungrouped v. grouped  ● Ungrouped frequencies deal with each score, while grouped frequencies have ranges  and intervals that group similar scores together  ○ Number of intervals: 10­20  ○ Width of intervals: 2,3, or multiples of 5  Histograms, frequency polygons, ogives, and stem­and­leaf plots  ● Histograms deal with both simple and relative frequencies, basic bar graph in which bars  must touch; frequencies are on y­axis and raw values are on x­axis  ● Frequency Polygons deal with both relative and simple frequencies; interchangeable use  with histograms; dots on graph are connected by a line, the line but touch the x­axis  twice  ● Ogives are graphs designed to show one cumulative frequencies; basically escalating  dots that are not connected  ● Stem­and­Leaf Plots show the shape of a distribution for individual scores in an interval  Chapter 3  Central tendency  ● Central tendency is the score around which all other scores cluster  Mean v. median v. mode  ● Mean is the average of all scores, and it is used when one is being the most accurate  ● Median is the value that divides the distribution in half, it includes rank and categorical  information only  ● Mode is the score that occurs the most, it is only categorical information   Range v. interquartile range  ● Range is the highest score minus the lowest score of a distribution while the interquartile  range is the subtraction of the 2nd quartile to the third  Average deviation v. variance and standard deviation  ● Average deviation is simply the average of all the deviation scores in a set of data  ● Variance is a method of calculating standard deviation from the means of a group  ● Standard deviation in the square root of the variance  Chapter 4  o  Bar charts and pie charts  ● Bar charts show noncontinuous data with no skewness or kurtosis; categorical  information  ● A sliced circle used to show percentages; rf is used more than f  o  Index of qualitative variation  ● A measure of statistical dispersion in nominal distribution  Chapter 5  Percentile rank  ● The percentile rank uses raw scores and converts them to cumulative relative frequency  ● It tells us the Standardized Scores (z­scores) and that estimates how far something is  from the mean  Characteristics of their distribution  ● Z­scores always have a variance and standard deviation of 1, and a summation and  mean of zero  Why they’re preferred over percentile ranks  ● S­scores allow one to compare two scores from different sets of distributions   


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